Trends and hot topics in radiology, nuclear medicine and medical imaging from 2011–2021: a bibliometric analysis of highly cited papers

• Published in: Japanese journal of radiology 2022-08, Vol.40 (8), p.847-856
• Main Authors: Yan, Sheng, Zhang, Huiting, Wang, Jun
• Format: Article
• Language: English
• Subjects: Artificial neural networks; Bibliometrics; Computed tomography; Coronaviruses; COVID-19; Deep learning; Imaging; Magnetic resonance imaging; Medical electronics; Medical imaging; Medical research; Medicine; Medicine & Public Health; Neural networks; Neuroimaging; Nuclear Medicine; Original; Original Article; Prostate cancer; Radiology; Radiotherapy; Trends; Viral diseases
• ISSN: 1867-1071; 1867-108X
• DOI: 10.1007/s11604-022-01268-z

Purpose To spotlight the trends and hot topics looming from the highly cited papers in the subject category of Radiology, Nuclear Medicine & Medical Imaging with bibliometric analysis. Materials and methods Based on the Essential Science Indicators, this study employed a bibliometric method to examine the highly cited papers in the subject category of Radiology, Nuclear Medicine & Medical Imaging in Web of Science (WoS) Categories, both quantitatively and qualitatively. In total, 1325 highly cited papers were retrieved and assessed spanning from the years of 2011 to 2021. In particular, the bibliometric information of the highly cited papers based on WoS database such as the main publication venues, the most productive countries, and the top cited publications was presented. An Abstract corpus was built to help identify the most frequently explored topics. VoSviewer was used to visualize the co-occurrence networks of author keywords. Results The top three active journals are Neuroimage, Radiology and IEEE T Med Imaging . The United States, Germany and England have the most influential publications. The top cited publications unrelated to COVID-19 can be grouped in three categories: recommendations or guidelines, processing software, and analysis methods . The top cited publications on COVID-19 are dominantly in China . The most frequently explored topics based on the Abstract corpus and the author keywords with the great link strengths overlap to a great extent. Specifically, phrases such as magnetic resonance imaging, deep learning, prostate cancer, chest CT, computed tomography, CT images, coronavirus disease, convolutional neural network(s) are among the most frequently mentioned. Conclusion The bibliometric analysis of the highly cited papers provided the most updated trends and hot topics which may provide insights and research directions for medical researchers and healthcare practitioners in the future.